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Lithography-free reconfigurable integrated photonic processor

Integrated photonics, because of its intrinsic high speed, large bandwidth and unlimited parallelism, is critical in the drive to ease the increasing data traffic. Its technological enabler is high-precision lithography, which allows for the fabrication of high-resolution photonic structures. Here,...

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Bibliographic Details
Published in:Nature photonics 2023-08, Vol.17 (8), p.710-716
Main Authors: Wu, Tianwei, Menarini, Marco, Gao, Zihe, Feng, Liang
Format: Article
Language:English
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Summary:Integrated photonics, because of its intrinsic high speed, large bandwidth and unlimited parallelism, is critical in the drive to ease the increasing data traffic. Its technological enabler is high-precision lithography, which allows for the fabrication of high-resolution photonic structures. Here, in complete contrast to the state of the art, where photonic functions are predefined by lithographically modulating the real index, we report a lithography-free paradigm for an integrated photonic processor, targeting dynamic control of spatial-temporal modulations of the imaginary index on an active semiconductor platform, without the need for lithography. We demonstrate an imaginary-index-driven methodology to tailor optical-gain distributions to rationally execute prescribed optical responses and configure desired photonic functionality to route and switch optical signals. Leveraging its real-time reconfigurability, we realize photonic neural networks with extraordinary flexibility, performing in situ training of vowel recognition with high accuracy. The programmability and multifunctionality intrinsically arising from the lithography-free characteristics can lead to a new paradigm for integrated photonic signal processing to conduct and reconfigure complex computation algorithms, accelerating the information-processing speed to achieve long-term performance requirements. Spatial light modulator-based lithography-free programmable light transmission through optical gain medium is demonstrated for optical switching and a rudimentary photonic neural network.
ISSN:1749-4885
1749-4893
DOI:10.1038/s41566-023-01205-0